Jinyan Wan

950 citations
18 papers · 734 · h-index 14

Impact in

Papers in

    • Traditional Chinese Medicine Analysis 4
    • Medicinal Plants and Neuroprotection 3
    • Barrier Structure and Function Studies 2
    • Neuroinflammation and Neurodegeneration Mechanisms 2
    • Neurological Disease Mechanisms and Treatments 2

Jinyan Wan

18 papers receiving 725 citations

Peers

Jinyan Wan
Comparison fields: 5 of 97
  • Biological Psychiatry 82
  • Complementary and alternative medicine 125
  • Neurology 106
  • Pharmacology 85
  • Behavioral Neuroscience 27
Replace Ai Shi with:
Ai Shi China
Rupinder Kaur Sodhi India
Aaina Singh Rathore India
Guangyue Su China
Rajesh R. Patil India
Sita Sharan Patel India
Bushra Shal Pakistan
Adnan Khan Pakistan
Arezoo Rajabian Iran
Ahmad Alhowail Saudi Arabia
Jinyan Wan relative to Ai Shi China Ai Shi's profile →
Citations per field
00.5×2.8×
Ai Shi · 1×
Citations per year

Countries citing papers authored by Jinyan Wan

Since Specialization
Citations

This map shows the geographic impact of Jinyan Wan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jinyan Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinyan Wan more than expected).

Fields of papers citing papers by Jinyan Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jinyan Wan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jinyan Wan. The network helps show where Jinyan Wan may publish in the future.

Co-authors

The 25 scholars most cited alongside Jinyan Wan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jinyan Wan Line = papers co-authored together Jinyan Wan links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2020142
2 2020127
3 202180
4 202277
5 202249
6 202047
7 202033
8 202231
9 202329
10 202227
11 202223
12 202216
13 202115
14 202113
15 202211
16 202311
17 20252
18 20251

About Jinyan Wan

Jinyan Wan is a scholar working on Complementary and alternative medicine, Neurology, Pharmacology, Molecular Biology and Biological Psychiatry, having authored 18 papers that have together received 734 indexed citations. Recurring topics across this work include Flavonoids in Medical Research (4 papers), Traditional Chinese Medicine Analysis (4 papers), Medicinal Plants and Neuroprotection (3 papers), Tryptophan and brain disorders (3 papers), Barrier Structure and Function Studies (2 papers), Catalytic C–H Functionalization Methods (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers) and Neurological Disease Mechanisms and Treatments (2 papers). The work is most often cited by research in Biological Psychiatry (82 citations), Complementary and alternative medicine (125 citations), Neurology (106 citations), Pharmacology (85 citations) and Behavioral Neuroscience (27 citations). Jinyan Wan has collaborated with scholars based in China and United States. Frequent co-authors include Yu Long, Nan Li, Yulu Zhang, Songyu Liu, Shuang Yu, Ai Shi, Wei Peng, Qiyue Yang, Xiang Yan and Songyu Liu. Their work appears in journals such as Pharmacological Research, Organic Letters, Frontiers in Pharmacology, Journal of Ethnopharmacology and AAPS PharmSciTech.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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